The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

The metabolic reprogramming evoked by nitrosative stress triggers the anaerobic utilization of citrate in Pseudomonas fluorescens.

Nitrosative stress is an ongoing challenge that most organisms have to contend with. When nitric oxide (NO) that may be generated either exogenously or endogenously encounters reactive oxygen species (ROS), it produces a set of toxic moieties referred to as reactive nitrogen species (RNS). As these RNS can severely damage essential biomolecules, numerous organisms have evolved elaborate detoxification strategies to nullify RNS. However, the contribution of cellular metabolism in fending off nitrosative stress is poorly understood. Using a variety of functional proteomic and metabolomic analyses, we have identified how the soil microbe Pseudomonas fluorescens reprogrammed its metabolic networks to survive in an environment enriched by sodium nitroprusside (SNP), a generator of nitrosative stress. To combat the RNS-induced ineffective aconitase (ACN) and tricarboxylic acid (TCA) cycle, the microbe invoked the participation of citrate lyase (CL), phosphoenolpyruvate carboxylase (PEPC) and pyruvate phosphate dikinase (PPDK) to convert citrate, the sole source of carbon into pyruvate and ATP. These enzymes were not evident in the control conditions. This metabolic shift was coupled to the concomitant increase in the activities of such classical RNS detoxifiers as nitrate reductase (NR), nitrite reductase (NIR) and S-nitrosoglutathione reductase (GSNOR). Hence, metabolism may hold the clues to the survival of organisms subjected to nitrosative stress and may provide therapeutic cues against RNS-resistant microbes

The Metabolic Reprogramming Evoked by Nitrosative Stress Triggers the Anaerobic Utilization of Citrate in

Nitrosative stress is an ongoing challenge that most organisms have to contend with. When nitric oxide (NO) that may be generated either exogenously or endogenously encounters reactive oxygen species (ROS), it produces a set of toxic moieties referred to as reactive nitrogen species (RNS). As these RNS can severely damage essential biomolecules, numerous organisms have evolved elaborate detoxification strategies to nullify RNS. However, the contribution of cellular metabolism in fending off nitrosative stress is poorly understood. Using a variety of functional proteomic and metabolomic analyses, we have identified how the soil microbe Pseudomonas fluorescens reprogrammed its metabolic networks to survive in an environment enriched by sodium nitroprusside (SNP), a generator of nitrosative stress. To combat the RNS-induced ineffective aconitase (ACN) and tricarboxylic acid (TCA) cycle, the microbe invoked the participation of citrate lyase (CL), phosphoenolpyruvate carboxylase (PEPC) and pyruvate phosphate dikinase (PPDK) to convert citrate, the sole source of carbon into pyruvate and ATP. These enzymes were not evident in the control conditions. This metabolic shift was coupled to the concomitant increase in the activities of such classical RNS detoxifiers as nitrate reductase (NR), nitrite reductase (NIR) and S-nitrosoglutathione reductase (GSNOR). Hence, metabolism may hold the clues to the survival of organisms subjecte

A Rigorous and Efficient Method To Reweight Very Large Conformational Ensembles Using Average Experimental Data and To Determine Their Relative Information Content

Flexible polypeptides such as unfolded proteins may access an astronomical number of conformations. The most advanced simulations of such states usually comprise tens of thousands of individual structures. In principle, a comparison of parameters predicted from such ensembles to experimental data provides a measure of their quality. In practice, analyses that go beyond the comparison of unbiased average data have been impossible to carry out on the entirety of such very large ensembles and have, therefore, been restricted to much smaller subensembles and/or nondeterministic algorithms. Here, we show that such very large ensembles, on the order of 10(4) to 10(5) conformations, can be analyzed in full by a maximum entropy fit to experimental average data. Maximizing the entropy of the population weights of individual conformations under experimental χ(2) constraints is a convex optimization problem, which can be solved in a very efficient and robust manner to a unique global solution even for very large ensembles. Since the population weights can be determined reliably, the reweighted full ensemble presents the best model of the combined information from simulation and experiment. Furthermore, since the reduction of entropy due to the experimental constraints is well-defined, its value provides a robust measure of the information content of the experimental data relative to the simulated ensemble and an indication for the density of the sampling of conformational space. The method is applied to the reweighting of a 35 000 frame molecular dynamics trajectory of the nonapeptide EGAAWAASS by extensive NMR (3)J coupling and RDC data. The analysis shows that RDCs provide significantly more information than (3)J couplings and that a discontinuity in the RDC pattern at the central tryptophan is caused by a cluster of helical conformations. Reweighting factors are moderate and consistent with errors in MD force fields of less than 3kT. The required reweighting is larger for an ensemble derived from a statistical coil model, consistent with its coarser nature. We call the method COPER, for convex optimization for ensemble reweighting. Similar advantages of large-scale efficiency and robustness can be obtained for other ensemble analysis methods with convex targets and constraints, such as constrained χ(2) minimization and the maximum occurrence method

RNS detoxifying mechanisms in <i>P. fluorescens</i>.

<p><i>A</i>, BN-PAGE analysis of NIR and NR from membrane CFE: ▪, control cultures; ▪, 10 mM SNP-treated cultures. Bands were quantified using SCION Imaging Software (n = 3, mean ± standard deviation). <i>B</i>, activity staining of GSNOR in soluble CFE (−, control cultures; <i>+</i>SNP, 10 mM SNP-treated cultures).</p

Oxaloacetate and PEP metabolism.

<p><i>A</i>, BN-PAGE analysis of oxaloacetate metabolizing enzymes. Bands were quantified using SCION Imaging Software (n = 3± standard deviation). <i>B</i>, In-cell Western blot analysis. <i>P.fluorescens</i> was grown to late logarithmic phase in 96 well plates then treated with control (−) and 10 mM SNP conditions for 24 h (+SNP). The cells were then analyzed for <b>(</b>GDH) and (PEPC) and expression was quantified by infrared fluorescence (n = 5, mean ± standard deviation. *p≤0.01). C, Citrate consumption in <i>P. fluorescens</i> exposed to ntirosative stress. Soluble CFE from 10 mM SNP-treated cells was incubated with 2 mM citrate, 1.0 mM Pi and 0.5 mM AMP for 30 min without (▪) and with an antibody (1∶500 dilution) against PEPC (□). n = 3, mean ± standard deviation. D, in-gel activity stain of the pyruvate generating enzymes PK and PPDK (−, control cultures; <i>+</i>SNP, 10 mM SNP-treated cultures).</p

Citrate metabolism in <i>Pseudomonas fluorescens</i> under nitrosative stress.

<p>Increased activity and expression of CL allows for the degradation of citrate and circumvention of nitrosative stress via a novel metabolic network in <i>P. fluorescens</i> subjected to SNP (⇓, decreased activity, ⇑, increased activity). CL, citrate lyase; AK, acetate kinase; ICDH, isocitrate dehydrogenase; MDH, malate dehydrogenase; PEPC, phosphoenolpyruvate carboxylase; PPDK, pyruvate phosphate dikinase; PDH, pyruvate dehydrogenase.</p

Influence of NO on the TCA cycle.

<p><i>A,</i> Representative chromatographs showing metabolite levels in soluble CFE from <i>P. fluorescens</i> grown in control and 10 mM SNP-containing cultures. <i>B,</i> In-gel activity analysis for ACN. <i>C</i>, in-gel activity staining of key metabolic enzymes. <i>D</i>, activity stains with sodium ferrocyanide as a control (−, control cultures; <i>+</i>SNP, 10 mM SNP-treated cultures; +SFC, 10 mM SFC-treated cultures).</p

Nitrosative stress in <i>P. fluorescens</i>.

<p><i>A,</i> cellular yield: ▴, control cultures; ♦, 5 mM SNP-containing cultures; •, 10 mM SNP-containing cultures; ▪, 15 mM SNP-containing cultures; □, 20 mM SNP-containing cultures. Nitrite/nitrate levels in spent fluids as measured by their absorbance at 540 nm after the Griess assay: □, control cultures; ▪, 5 mM SNP-containing cultures; ▪, 10 mM SNP-containing cultures. <i>B</i>, In cell Western blot analysis of <i>P. fluorescens</i> under nitrosative stress. <i>P. fluorescens</i> was grown to late logarithmic phase in 96 well plates and then treated with control (−) and 10 mM SNP conditions for 24 h (+SNP). Following treatment, control cells were placed in media containing 10 mM SNP for 8 h (Ctl→SNP) and 10 mM SNP-treated cells were recovered with control media for 8 h (SNP→Ctl). Total protein concentration was assessed by the Bradford assay. The cells were then analyzed for expression of nitrosylated tyrosine residues by quantification of infrared fluorescence (n = 3. *p≤0.01, mean ± standard deviation).</p